R-CONV++: uncovering privacy vulnerabilities through analytical gradient inversion attacks
<p dir="ltr">Federated learning has emerged as a prominent privacy-preserving technique for leveraging large-scale distributed datasets by sharing gradients instead of raw data. However, recent studies indicate that private training data can still be exposed through gradient inversio...
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2025
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